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👋 Hi, I’m @m-ulmestrand, but you can call me Mattias.
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👀 I do a lot of Machine Learning in my spare time as well as at work. I'm especially interested in Graph Neural Networks. I find them useful and fascinating, since a lot of physical structures can be modelled as graphs. I have a repository open where I have used a GCN to learn collision physics in multi-particle collisions. I also made a self-learning game with LSTM and Deep Q-learning, where agents learn to avoid the predator (player) in real time. Another project I did features self-driving cars with Deep Q-learning and LiDAR-like detectors
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🌱 I work as a Machine Learning and Computer Vision engineer at Taigatech. Previously I studied the Master's programme Complex Adaptive Systems at Chalmers University of Technology where I predominantly took courses in Machine Learning and Computational engineering. Before that I studied Engineering Physics for three years. I also conducted exchange studies to ETH Zürich, where I continued with the same profile. Having a background in both Computational engineering and ML, I like to do projects where I get to combine the modelling-intensive character of Computational engineering and the data-centred approach of ML. Most of my projects have such an approach, where I model an environment from the ground up and let an ML algorithm learn from it.
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💞️ I’d love to collaborate on ML projects, especially with applications for physics, programming or games.
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📫 Reach me at m.ulmestrand@gmail.com.
- Gothenburg, Sweden
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self-driving-ai
self-driving-ai PublicThis project explores making a model of a car self-driving. The model is controlled by a neural network which is trained with Q-learning. The entire environment, from collision detection to buildin…
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gcn-collisions
gcn-collisions PublicThis Graph Convolutional Network learns to simulate collision responses for particles. Speedups can be seen for large numbers of particles. The network can also learn to account for symmetry-breaki…
Python 3
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interactive-AI-game
interactive-AI-game PublicThis game lets the player control a predator, whose objective is to devour prey agents. The agents learn to avoid the player from experience in real time. The agents are controlled by an LSTM which…
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art-ificial-intelligence
art-ificial-intelligence PublicThis is a master's project in advanced machine learning with neural networks. We investigated CycleGANs for generating art of different styles, compared different architectures and improved upon th…
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